Welcome!

Machine Learning Authors: Yeshim Deniz, Pat Romanski, Liz McMillan, Elizabeth White, Corey Roth

News Feed Item

DataStax Hires Clint Smith as General Counsel

Responsible for All Legal Matters as Company Undergoes Significant Revenue, International, Channel and Headcount Expansion

SAN MATEO, CA -- (Marketwired) -- 01/15/14 -- DataStax, the company that powers the online applications that transform business, today announced it has hired Clint Smith as general counsel, responsible for the company's legal affairs, including corporate law, intellectual property strategy, commercial contracts, compliance and litigation. Smith previously has headed the legal departments at UUNET, Macromedia and TrialPay and served as general counsel at open source database provider MySQL AB where he helped lead the company through its $1B acquisition by Sun Microsystems in 2008.

"DataStax is growing very quickly, with significant revenue, international, channel and headcount expansion expected in 2014," said Billy Bosworth, CEO, DataStax. "Clint's deep experience with open-source technologies and corporate law will help take us to the next level as we address the huge opportunity within the operational database market."

DataStax sells an enterprise-grade NoSQL database that seamlessly and securely integrates real-time data with Apache Cassandra, batch analytics, enterprise search, as well as visual monitoring and management. The integration allows enterprises to leverage their hot data in real-time, in the context of their critical business application. DataStax powers applications for more than 300 customers, including eBay, Netflix, Adobe, Constant Contact and Ooyala, as well as 21 companies within the Fortune 100.

DataStax received $45 million in a Series-D round of funding in July 2013, and since then has broadened its leadership team by hiring Dennis Wolf as chief financial officer, and now Smith as general counsel. Smith received his bachelor's degree from Pomona College, and his master's degree and J.D. from UC Berkeley. He began his career at the law firm of Steptoe & Johnson LLP, has held leadership positions with national trade associations including the Business Software Alliance and the U.S. Internet Service Provider Association, and is a regular speaker on technology law topics.

About DataStax
DataStax powers the online applications that transform business for more than 300 customers, including startups and 21 of the Fortune 100. DataStax delivers a massively scalable, flexible and continuously available big data platform built on Apache Cassandra™. DataStax integrates enterprise-ready Cassandra, Apache Hadoop™ for analytics and Apache Solr™ for search across multi-datacenters and in the cloud.

Companies such as Adobe, Healthcare Anytime, eBay and Netflix rely on DataStax to transform their businesses. Based in San Mateo, Calif., DataStax is backed by industry-leading investors: Lightspeed Venture Partners, Crosslink Capital, Meritech Capital Partners, Scale Venture Partners, DFJ Growth and Next World Capital. For more information, visit DataStax or follow us @DataStax and @DataStaxEU.

Alex Bradley
Email Contact
408-599-8457

More Stories By Marketwired .

Copyright © 2009 Marketwired. All rights reserved. All the news releases provided by Marketwired are copyrighted. Any forms of copying other than an individual user's personal reference without express written permission is prohibited. Further distribution of these materials is strictly forbidden, including but not limited to, posting, emailing, faxing, archiving in a public database, redistributing via a computer network or in a printed form.

CloudEXPO Stories
The best way to leverage your Cloud Expo presence as a sponsor and exhibitor is to plan your news announcements around our events. The press covering Cloud Expo and @ThingsExpo will have access to these releases and will amplify your news announcements. More than two dozen Cloud companies either set deals at our shows or have announced their mergers and acquisitions at Cloud Expo. Product announcements during our show provide your company with the most reach through our targeted audiences.
DXWorldEXPO LLC announced today that Telecom Reseller has been named "Media Sponsor" of CloudEXPO | DXWorldEXPO 2018 New York, which will take place on November 11-13, 2018 in New York City, NY. Telecom Reseller reports on Unified Communications, UCaaS, BPaaS for enterprise and SMBs. They report extensively on both customer premises based solutions such as IP-PBX as well as cloud based and hosted platforms.
Enterprises are striving to become digital businesses for differentiated innovation and customer-centricity. Traditionally, they focused on digitizing processes and paper workflow. To be a disruptor and compete against new players, they need to gain insight into business data and innovate at scale. Cloud and cognitive technologies can help them leverage hidden data in SAP/ERP systems to fuel their businesses to accelerate digital transformation success.
When building large, cloud-based applications that operate at a high scale, it's important to maintain a high availability and resilience to failures. In order to do that, you must be tolerant of failures, even in light of failures in other areas of your application. "Fly two mistakes high" is an old adage in the radio control airplane hobby. It means, fly high enough so that if you make a mistake, you can continue flying with room to still make mistakes. In his session at 18th Cloud Expo, Lee Atchison, Principal Cloud Architect and Advocate at New Relic, discussed how this same philosophy can be applied to highly scaled applications, and can dramatically increase your resilience to failure.
Machine learning provides predictive models which a business can apply in countless ways to better understand its customers and operations. Since machine learning was first developed with flat, tabular data in mind, it is still not widely understood: when does it make sense to use graph databases and machine learning in combination? This talk tackles the question from two ends: classifying predictive analytics methods and assessing graph database attributes. It also examines the ongoing lifecycle for machine learning in production. From this analysis it builds a framework for seeing where machine learning on a graph can be advantageous.'